Abstract
Desert locust swarms intermittently damage crops and pastures in sixty countries from Africa to western Asia, threatening the food security of 10% of the world’s population. During the 20th century, desert locust control operations began organizing, and nowadays, they are coordinated by the Food and Agriculture Organization (FAO), which promotes a preventative strategy based on early warning and rapid response. This strategy implies a constant monitoring of the populations and of the ecological conditions favorable to their development. Satellite remote sensing can provide a near real-time monitoring of these conditions at the continental scale. Thus, the desert locust control community needs a reliable detection of green vegetation in arid and semi-arid areas as an indicator of potential desert locust habitat. To meet this need, a colorimetric transformation has been developed on both SPOT-VEGETATION and MODIS data to produce dynamic greenness maps. After their integration in the daily locust control activities, this research aimed at assessing those dynamic greenness maps from the producers’ and the users’ points of view. Eight confusion matrices and Pareto boundaries were derived from high resolution reference maps representative of the temporal and spatial diversity of Mauritanian habitats. The dynamic greenness maps were found to be accurate in summer breeding areas (F-score = 0.64–0.87), but accuracy dropped in winter breeding areas (F-score = 0.28–0.40). Accuracy is related to landscape fragmentation (R2 = 0.9): the current spatial resolution remains too coarse to resolve complex fragmented patterns and accounts for a substantial (60%) part of the error. The exploitation of PROBA-V 100-m images at the finest resolution (100-m) would enhance by 20% the vegetation detection in fragmented habitat. A survey revealed that end-users are satisfied with the product and find it fit for monitoring, thanks to an intuitive interpretation, leading to more efficiency.
Highlights
The food security of sixty countries from Northern Africa to India is often threatened by desert locusts, Schistocerca gregaria (Forksål, 1775)
This paper aimed at assessing the relevance of the dynamic greenness map product for near real-time operational monitoring of the desert locust habitat
The methodology is based on a colorimetric transformation and a set of thresholds defined by statistical sampling
Summary
The food security of sixty countries from Northern Africa to India is often threatened by desert locusts, Schistocerca gregaria (Forksål, 1775). This notorious insect pest [1] has the ability to form swarms of billions of individuals that damage crops and pastures. Their devastating effects lead to numerous socio-economic consequences for a tenth of the world population [2]. Damages diminished harvest from 80%–100% [3]. To contain this pest, 13 million hectares have been sprayed in
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